Integrating Big Data And Cloud Solutions: Strategies For Efficient And Scalable Implementation

Abstract

Big Data and cloud solutions have come a long way, helping each other with all the advancements that have happened in a span of no time. With numerous technological advancements at practically negligible costs that cloud platforms provide, it became easy to store huge volumes of data on the server and also quickly interact with such huge data to perform various analytics at different levels that Big Data asks for.

Along with some of the immediate practical complexities of storing, quickly fetching, and performing analytics on such huge data implementations themselves, numerous questions are also raised concerning privacy, security, integrity, and various other dimensions. Implementation of practical complex systems handling Big Data at one end and cloud technological advancement at the other end sensitizes the engineering community to consider various dimensions to maintain the balance between architectural intricacies and security posture for efficient and scalable implementation of Big Data and cloud solutions. This tutorial is devoted to providing the engineering community with installing the best practices in implementing practical and complex strategies about privacy, security, and integrity, and lined with legal perspectives, for enabling efficient, transparent, and scalable Big Data implementation on one side and taking the advantages of cloud solutions on the other side.